High dynamic range (HDR) imaging is about representing scenes with values commensurate with real-world light levels. The real world produces a twelve order of magnitude range of light intensity variation, which is much greater than the three orders of magnitude common in current digital imaging. The range of values each pixel can currently represent in a digital image is typically 256 values per color channel (with a maximum of 65536 values), which is inadequate for representing many scenes. It is better to capture scenes with a range of light intensities representative of the scene and range of values matched to the limits of human vision, rather than matched to any display device. Such images are called HDR images. Images suitable for display with current display technology are called Low Dynamic Range (LDR) images. The visual quality of high dynamic range images is much higher than that of conventional low dynamic range images.
HDR images are different from LDR images regarding the capture, storage, processing, and display of such images, and are rapidly gaining wide acceptance in photography. Although HDR display technology will become generally available in the near future, it will take time before most users have made the transition. At the same time, printed media will never become HDR. As a result, there will always be a need to prepare HDR imagery for display on LDR devices. The process of reducing the range of values in an HDR image such that the result becomes displayable in a meaningful way is called dynamic range reduction. Algorithms that prepare HDR images for display on LDR display devices by achieving dynamic range reduction are called tone reproduction or simply tone-mapping operators. Therefore, tone mapping converts HDR images into an 8-bit representation suitable for rendering on LDR displays. It reduces the dynamic range of the image while preserving a good contrast level for the brightly and darkly illuminated regions.
Professional or consumer digital photography devices, equipped with commodity processors, that can capture and process HDR images will be the norm in the near future. HDR sensors already exists; e.g., Fraunhofer-Institut Milkroelelronische Schaltungen und Systeme. CMOS image sensor with 118 dB linear dynamic input range Data Sheet. A major requirement for such devices will be the ability to perform dynamic range reduction through tone mapping, in real time or near real time. Photographic quality tone-mapping, which is a local adaptive operation, requires intensive computation that cannot be processed in real time (or near real time) on digital photographic devices unless such computation is performed efficiently on a powerful commodity processor. Therefore, an efficient technique that can perform tone mapping for real time (or near real time) HDR video and interactive still photography, using a commodity processor on digital photographic devices, is needed.
Currently there exist some HDR photographic quality tone mapping local operators. The most known operator for its high photographic quality is Reinhard et al. photographic tone mapping operator (Erik Reinhard, Michael Stark, Peter Shirley, and James Ferwerda. Photographic tone reproduction for digital images, SIGGRAPH '02: Proceedings of the 29th annual conference on Computer graphics and interactive techniques, pages 267-276, New York, N.Y., USA, 2002. ACM Press), which is a local adaptive operator incorporating the classical Ansel Adams dodging-and-burning technique (Ansel Adams, The Print, The Ansel Adams Photography Series/Book 3, Little, Brown and Company, tenth edition, 2003, with the collaboration of Robert Balker), that is based on common photographic principles, to tone map each individual pixel of the HDR image. This local tone mapping operator, like the other currently available local operators, runs only offline on workstations, as local operators require huge computation.